Sequences and events used for training and testing. by Johanna K. Theuer (19942849)

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Fig 5 - by Johanna K. Theuer (19942849)

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Fig 6 - by Johanna K. Theuer (19942849)

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Schematic representation of the CAPRI² model. by Johanna K. Theuer (19942849)

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Comparison of infant and model data. by Johanna K. Theuer (19942849)

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(a) Cluster of Interest Extracted from the Clustered Image; (b) Cluster of Interest converted into Grey Scale; (c) Grey Scale Image Converted into Black/White; (d) Object of Intere... by Claudia Barile (20678698)

Average CA for HT, FWHT, BP, and SF-based features extracted from 2.4-second time segments using the k-NN classifier. by Ebru Ergün (21395498)

DataSheet1_Barrier-free tomato fruit selection and location based on optimized semantic segmentation and obstacle perception algorithm.docx by Lingli Zhou (539752)

“…The improved semantic segmentation algorithm significantly increased the segmentation accuracy of linear-structured obstacles, and the obstacle perception algorithm effectively avoided occluded fruits. …”

Average CA Results for 24-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 12-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 4.8-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 2.4-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Segmented retinal vessels and optic disc. by Chaoyang Zhao (588743)

Cell-TRACTR detects cells in the first frame at time t 0. Object queries predicted to be a “cell” are converted to track queries. For Track Group Denoising (TGD), random noise is a... by Owen M. O’Connor (11965460)

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Training configurations of the utilized datasets. by Zhuolin Yang (14658411)

“…This may cause some effective information to be mistaken for redundant information and discarded, which in turn causes object segmentation confusion. As a convolutional layer deepens, the loss of spatial detail information makes the segmentation effect achieved at the object boundary insufficiently accurate. …”

Code and raw data used in this study. by Zhuolin Yang (14658411)

“…This may cause some effective information to be mistaken for redundant information and discarded, which in turn causes object segmentation confusion. As a convolutional layer deepens, the loss of spatial detail information makes the segmentation effect achieved at the object boundary insufficiently accurate. …”

Performance of the model on the validation dataset of EFSI. by Anna Demchenko (18449439)

Depiction of how predictions are made from the output embeddings. The largest encoded multi-scale feature map is resized and combined with the original multi-scale features to form... by Owen M. O’Connor (11965460)

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Membership functions for speed and distance in the 41–43 m section. by Seung-Min Ryu (21463891)

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Fuzzy rules generated by the adaptive neuro–fuzzy inference system. by Seung-Min Ryu (21463891)

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